Judges Votes Report

Dataset statistics

Number of variables	27
Number of observations	39
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	10.5 KiB
Average record size in memory	275.8 B

Variable types

Categorical	8
Numeric	19

Warnings

`United Kingdom` has constant value "0"	Constant
`Greece` is highly correlated with `Iceland`	High correlation
`Iceland` is highly correlated with `Greece` and 1 other fields	High correlation
`Moldova` is highly correlated with `Iceland` and 1 other fields	High correlation
`Switzerland` is highly correlated with `Moldova`	High correlation
`Greece` is highly correlated with `Iceland`	High correlation
`Iceland` is highly correlated with `Greece` and 1 other fields	High correlation
`Moldova` is highly correlated with `Iceland`	High correlation
`Belgium` is highly correlated with `Ukraine` and 3 other fields	High correlation
`Israel` is highly correlated with `Norway` and 5 other fields	High correlation
`Greece` is highly correlated with `Country (Voters (vertical), Finalists (horizontal))` and 4 other fields	High correlation
`Ukraine` is highly correlated with `Belgium` and 4 other fields	High correlation
`Norway` is highly correlated with `Israel` and 2 other fields	High correlation
`Albania` is highly correlated with `Norway` and 5 other fields	High correlation
`France` is highly correlated with `Country (Voters (vertical), Finalists (horizontal))` and 4 other fields	High correlation
`Lithuania` is highly correlated with `Country (Voters (vertical), Finalists (horizontal))`	High correlation
`Country (Voters (vertical), Finalists (horizontal))` is highly correlated with `Belgium` and 24 other fields	High correlation
`Bulgaria` is highly correlated with `Albania` and 5 other fields	High correlation
`Switzerland` is highly correlated with `Belgium` and 5 other fields	High correlation
`Germany` is highly correlated with `France` and 5 other fields	High correlation
`Iceland` is highly correlated with `Israel` and 4 other fields	High correlation
`Russia` is highly correlated with `Greece` and 4 other fields	High correlation
`Italy` is highly correlated with `Ukraine` and 4 other fields	High correlation
`Malta` is highly correlated with `Belgium` and 6 other fields	High correlation
`Moldova` is highly correlated with `Greece` and 9 other fields	High correlation
`Finland` is highly correlated with `Greece` and 3 other fields	High correlation
`Sweden` is highly correlated with `Israel` and 6 other fields	High correlation
`Netherlands` is highly correlated with `Ukraine` and 1 other fields	High correlation
`Serbia` is highly correlated with `Country (Voters (vertical), Finalists (horizontal))` and 2 other fields	High correlation
`Spain` is highly correlated with `Israel` and 3 other fields	High correlation
`San Marino` is highly correlated with `Israel` and 6 other fields	High correlation
`Cyprus` is highly correlated with `France` and 4 other fields	High correlation
`Portugal` is highly correlated with `Country (Voters (vertical), Finalists (horizontal))` and 3 other fields	High correlation
`Azerbaijan` is highly correlated with `France` and 3 other fields	High correlation
`Albania` is highly correlated with `Country (Voters (vertical), Finalists (horizontal))` and 1 other fields	High correlation
`Country (Voters (vertical), Finalists (horizontal))` is highly correlated with `Albania` and 6 other fields	High correlation
`Netherlands` is highly correlated with `Country (Voters (vertical), Finalists (horizontal))` and 1 other fields	High correlation
`Germany` is highly correlated with `Country (Voters (vertical), Finalists (horizontal))` and 1 other fields	High correlation
`Serbia` is highly correlated with `Country (Voters (vertical), Finalists (horizontal))` and 1 other fields	High correlation
`Spain` is highly correlated with `Country (Voters (vertical), Finalists (horizontal))` and 1 other fields	High correlation
`United Kingdom` is highly correlated with `Albania` and 6 other fields	High correlation
`Norway` is highly correlated with `Country (Voters (vertical), Finalists (horizontal))` and 1 other fields	High correlation
`Country (Voters (vertical), Finalists (horizontal))` is uniformly distributed	Uniform
`Country (Voters (vertical), Finalists (horizontal))` has unique values	Unique
`Azerbaijan` has 30 (76.9%) zeros	Zeros
`Belgium` has 22 (56.4%) zeros	Zeros
`Bulgaria` has 13 (33.3%) zeros	Zeros
`Cyprus` has 28 (71.8%) zeros	Zeros
`Finland` has 20 (51.3%) zeros	Zeros
`France` has 6 (15.4%) zeros	Zeros
`Greece` has 24 (61.5%) zeros	Zeros
`Iceland` has 11 (28.2%) zeros	Zeros
`Israel` has 22 (56.4%) zeros	Zeros
`Italy` has 11 (28.2%) zeros	Zeros
`Lithuania` has 27 (69.2%) zeros	Zeros
`Malta` has 4 (10.3%) zeros	Zeros
`Moldova` has 33 (84.6%) zeros	Zeros
`Portugal` has 17 (43.6%) zeros	Zeros
`Russia` has 18 (46.2%) zeros	Zeros
`San Marino` has 32 (82.1%) zeros	Zeros
`Sweden` has 29 (74.4%) zeros	Zeros
`Switzerland` has 5 (12.8%) zeros	Zeros
`Ukraine` has 20 (51.3%) zeros	Zeros

Reproduction

Analysis started	2021-05-30 15:58:27.615365
Analysis finished	2021-05-30 16:01:03.102447
Duration	2 minutes and 35.49 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

Country (Voters (vertical), Finalists (horizontal))
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	39
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	2.6 KiB

Italy	1
Greece	1
Ukraine	1
Bulgaria	1
Israel	1
Other values (34)	34

Length

Max length	15
Median length	7
Mean length	7.512820513
Min length	5

Characters and Unicode

Total characters	293
Distinct characters	40
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	39 ?
Unique (%)	100.0%

Sample

1st row	Albania
2nd row	Australia
3rd row	Austria
4th row	Azerbaijan
5th row	Belgium

Common Values

Value	Count	Frequency (%)
Italy	1	2.6%
Greece	1	2.6%
Ukraine	1	2.6%
Bulgaria	1	2.6%
Israel	1	2.6%
Germany	1	2.6%
Australia	1	2.6%
Slovenia	1	2.6%
Switzerland	1	2.6%
Austria	1	2.6%
Other values (29)	29	74.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
czechia	1	2.4%
sweden	1	2.4%
azerbaijan	1	2.4%
north	1	2.4%
estonia	1	2.4%
russia	1	2.4%
latvia	1	2.4%
spain	1	2.4%
greece	1	2.4%
australia	1	2.4%
Other values (32)	32	76.2%

Most occurring characters

Value	Count	Frequency (%)
a	45	15.4%
i	25	8.5%
n	24	8.2%
e	23	7.8%
r	21	7.2%
l	16	5.5%
o	14	4.8%
t	13	4.4%
d	11	3.8%
u	8	2.7%
Other values (30)	93	31.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	248	84.6%
Uppercase Letter	42	14.3%
Space Separator	3	1.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	45	18.1%
i	25	10.1%
n	24	9.7%
e	23	9.3%
r	21	8.5%
l	16	6.5%
o	14	5.6%
t	13	5.2%
d	11	4.4%
u	8	3.2%
Other values (13)	48	19.4%

Uppercase Letter

Value	Count	Frequency (%)
S	6	14.3%
A	4	9.5%
I	4	9.5%
M	4	9.5%
C	3	7.1%
G	3	7.1%
N	3	7.1%
B	2	4.8%
F	2	4.8%
L	2	4.8%
Other values (6)	9	21.4%

Space Separator

Value	Count	Frequency (%)
	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	290	99.0%
Common	3	1.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	45	15.5%
i	25	8.6%
n	24	8.3%
e	23	7.9%
r	21	7.2%
l	16	5.5%
o	14	4.8%
t	13	4.5%
d	11	3.8%
u	8	2.8%
Other values (29)	90	31.0%

Common

Value	Count	Frequency (%)
	3	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	293	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	45	15.4%
i	25	8.5%
n	24	8.2%
e	23	7.8%
r	21	7.2%
l	16	5.5%
o	14	4.8%
t	13	4.4%
d	11	3.8%
u	8	2.7%
Other values (30)	93	31.7%

Albania
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	12.8%
Missing	0
Missing (%)	0.0%
Memory size	2.3 KiB

0	35
7	1
1	1
12	1
2	1

Length

Max length	2
Median length	1
Mean length	1.025641026
Min length	1

Characters and Unicode

Total characters	40
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	10.3%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	35	89.7%
7	1	2.6%
1	1	2.6%
12	1	2.6%
2	1	2.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	35	89.7%
7	1	2.6%
1	1	2.6%
12	1	2.6%
2	1	2.6%

Most occurring characters

Value	Count	Frequency (%)
0	35	87.5%
1	2	5.0%
2	2	5.0%
7	1	2.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	40	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	35	87.5%
1	2	5.0%
2	2	5.0%
7	1	2.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	40	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	35	87.5%
1	2	5.0%
2	2	5.0%
7	1	2.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	40	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	35	87.5%
1	2	5.0%
2	2	5.0%
7	1	2.5%

Azerbaijan
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	6
Distinct (%)	15.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.8205128205

Minimum	0
Maximum	8
Zeros	30
Zeros (%)	76.9%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	5.1
Maximum	8
Range	8
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.833486682
Coefficient of variation (CV)	2.234561894
Kurtosis	6.913746205
Mean	0.8205128205
Median Absolute Deviation (MAD)	0
Skewness	2.628250023
Sum	32
Variance	3.361673414
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	30	76.9%
2	5	12.8%
3	1	2.6%
5	1	2.6%
6	1	2.6%
8	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	30	76.9%
2	5	12.8%
3	1	2.6%
5	1	2.6%
6	1	2.6%
8	1	2.6%

Value	Count	Frequency (%)
8	1	2.6%
6	1	2.6%
5	1	2.6%
3	1	2.6%
2	5	12.8%
0	30	76.9%

Belgium
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	7
Distinct (%)	17.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.820512821

Minimum	0
Maximum	7
Zeros	22
Zeros (%)	56.4%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	3
95-th percentile	6
Maximum	7
Range	7
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	2.41564849
Coefficient of variation (CV)	1.326905508
Kurtosis	-0.7844709133
Mean	1.820512821
Median Absolute Deviation (MAD)	0
Skewness	0.8946069093
Sum	71
Variance	5.835357625
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	22	56.4%
3	6	15.4%
6	5	12.8%
1	2	5.1%
5	2	5.1%
4	1	2.6%
7	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	22	56.4%
1	2	5.1%
3	6	15.4%
4	1	2.6%
5	2	5.1%
6	5	12.8%
7	1	2.6%

Value	Count	Frequency (%)
7	1	2.6%
6	5	12.8%
5	2	5.1%
4	1	2.6%
3	6	15.4%
1	2	5.1%
0	22	56.4%

Bulgaria
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	10
Distinct (%)	25.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.58974359

Minimum	0
Maximum	12
Zeros	13
Zeros (%)	33.3%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	3
Q3	6
95-th percentile	10.2
Maximum	12
Range	12
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	3.632586064
Coefficient of variation (CV)	1.011934689
Kurtosis	-0.3014629518
Mean	3.58974359
Median Absolute Deviation (MAD)	3
Skewness	0.7625982933
Sum	140
Variance	13.19568151
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	13	33.3%
6	6	15.4%
5	4	10.3%
1	3	7.7%
2	3	7.7%
4	3	7.7%
8	2	5.1%
10	2	5.1%
12	2	5.1%
3	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	13	33.3%
1	3	7.7%
2	3	7.7%
3	1	2.6%
4	3	7.7%
5	4	10.3%
6	6	15.4%
8	2	5.1%
10	2	5.1%
12	2	5.1%

Value	Count	Frequency (%)
12	2	5.1%
10	2	5.1%
8	2	5.1%
6	6	15.4%
5	4	10.3%
4	3	7.7%
3	1	2.6%
2	3	7.7%
1	3	7.7%
0	13	33.3%

Cyprus
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	8
Distinct (%)	20.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.282051282

Minimum	0
Maximum	12
Zeros	28
Zeros (%)	71.8%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1.5
95-th percentile	7
Maximum	12
Range	12
Interquartile range (IQR)	1.5

Descriptive statistics

Standard deviation	2.655170903
Coefficient of variation (CV)	2.071033304
Kurtosis	6.68423438
Mean	1.282051282
Median Absolute Deviation (MAD)	0
Skewness	2.515341235
Sum	50
Variance	7.049932524
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	28	71.8%
2	3	7.7%
4	2	5.1%
7	2	5.1%
1	1	2.6%
3	1	2.6%
6	1	2.6%
12	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	28	71.8%
1	1	2.6%
2	3	7.7%
3	1	2.6%
4	2	5.1%
6	1	2.6%
7	2	5.1%
12	1	2.6%

Value	Count	Frequency (%)
12	1	2.6%
7	2	5.1%
6	1	2.6%
4	2	5.1%
3	1	2.6%
2	3	7.7%
1	1	2.6%
0	28	71.8%

Finland
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	9
Distinct (%)	23.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.128205128

Minimum	0
Maximum	10
Zeros	20
Zeros (%)	51.3%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	3.5
95-th percentile	8.2
Maximum	10
Range	10
Interquartile range (IQR)	3.5

Descriptive statistics

Standard deviation	3.113463862
Coefficient of variation (CV)	1.462952899
Kurtosis	0.7929404852
Mean	2.128205128
Median Absolute Deviation (MAD)	0
Skewness	1.418344186
Sum	83
Variance	9.69365722
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	20	51.3%
1	5	12.8%
4	3	7.7%
8	3	7.7%
2	2	5.1%
3	2	5.1%
10	2	5.1%
5	1	2.6%
7	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	20	51.3%
1	5	12.8%
2	2	5.1%
3	2	5.1%
4	3	7.7%
5	1	2.6%
7	1	2.6%
8	3	7.7%
10	2	5.1%

Value	Count	Frequency (%)
10	2	5.1%
8	3	7.7%
7	1	2.6%
5	1	2.6%
4	3	7.7%
3	2	5.1%
2	2	5.1%
1	5	12.8%
0	20	51.3%

France
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	10
Distinct (%)	25.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.358974359

Minimum	0
Maximum	12
Zeros	6
Zeros (%)	15.4%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3.5
median	6
Q3	10
95-th percentile	12
Maximum	12
Range	12
Interquartile range (IQR)	6.5

Descriptive statistics

Standard deviation	4.094201159
Coefficient of variation (CV)	0.64384615
Kurtosis	-1.112957507
Mean	6.358974359
Median Absolute Deviation (MAD)	3
Skewness	-0.06376964086
Sum	248
Variance	16.76248313
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
12	8	20.5%
0	6	15.4%
7	5	12.8%
4	4	10.3%
6	4	10.3%
10	4	10.3%
3	3	7.7%
5	2	5.1%
8	2	5.1%
2	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	6	15.4%
2	1	2.6%
3	3	7.7%
4	4	10.3%
5	2	5.1%
6	4	10.3%
7	5	12.8%
8	2	5.1%
10	4	10.3%
12	8	20.5%

Value	Count	Frequency (%)
12	8	20.5%
10	4	10.3%
8	2	5.1%
7	5	12.8%
6	4	10.3%
5	2	5.1%
4	4	10.3%
3	3	7.7%
2	1	2.6%
0	6	15.4%

Germany
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	7.7%
Missing	0
Missing (%)	0.0%
Memory size	2.3 KiB

0	37
1	1
2	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	39
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	5.1%

Sample

1st row	0
2nd row	0
3rd row	2
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	37	94.9%
1	1	2.6%
2	1	2.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	37	94.9%
1	1	2.6%
2	1	2.6%

Most occurring characters

Value	Count	Frequency (%)
0	37	94.9%
2	1	2.6%
1	1	2.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	39	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	37	94.9%
2	1	2.6%
1	1	2.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	39	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	37	94.9%
2	1	2.6%
1	1	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	39	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	37	94.9%
2	1	2.6%
1	1	2.6%

Greece
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	10
Distinct (%)	25.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.333333333

Minimum	0
Maximum	12
Zeros	24
Zeros (%)	61.5%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	3.5
95-th percentile	10.2
Maximum	12
Range	12
Interquartile range (IQR)	3.5

Descriptive statistics

Standard deviation	3.729916983
Coefficient of variation (CV)	1.59853585
Kurtosis	0.8199676947
Mean	2.333333333
Median Absolute Deviation (MAD)	0
Skewness	1.442669314
Sum	91
Variance	13.9122807
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	24	61.5%
8	3	7.7%
1	2	5.1%
3	2	5.1%
6	2	5.1%
12	2	5.1%
2	1	2.6%
4	1	2.6%
7	1	2.6%
10	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	24	61.5%
1	2	5.1%
2	1	2.6%
3	2	5.1%
4	1	2.6%
6	2	5.1%
7	1	2.6%
8	3	7.7%
10	1	2.6%
12	2	5.1%

Value	Count	Frequency (%)
12	2	5.1%
10	1	2.6%
8	3	7.7%
7	1	2.6%
6	2	5.1%
4	1	2.6%
3	2	5.1%
2	1	2.6%
1	2	5.1%
0	24	61.5%

Iceland
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	10
Distinct (%)	25.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.076923077

Minimum	0
Maximum	12
Zeros	11
Zeros (%)	28.2%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	5
Q3	8
95-th percentile	10
Maximum	12
Range	12
Interquartile range (IQR)	8

Descriptive statistics

Standard deviation	3.969519495
Coefficient of variation (CV)	0.781875052
Kurtosis	-1.462345627
Mean	5.076923077
Median Absolute Deviation (MAD)	3
Skewness	-0.05995521357
Sum	198
Variance	15.75708502
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	11	28.2%
8	7	17.9%
10	7	17.9%
3	3	7.7%
4	3	7.7%
7	3	7.7%
5	2	5.1%
2	1	2.6%
6	1	2.6%
12	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	11	28.2%
2	1	2.6%
3	3	7.7%
4	3	7.7%
5	2	5.1%
6	1	2.6%
7	3	7.7%
8	7	17.9%
10	7	17.9%
12	1	2.6%

Value	Count	Frequency (%)
12	1	2.6%
10	7	17.9%
8	7	17.9%
7	3	7.7%
6	1	2.6%
5	2	5.1%
4	3	7.7%
3	3	7.7%
2	1	2.6%
0	11	28.2%

Israel
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	9
Distinct (%)	23.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.871794872

Minimum	0
Maximum	8
Zeros	22
Zeros (%)	56.4%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	4
95-th percentile	7.1
Maximum	8
Range	8
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.617546935
Coefficient of variation (CV)	1.398415486
Kurtosis	-0.155325655
Mean	1.871794872
Median Absolute Deviation (MAD)	0
Skewness	1.10311177
Sum	73
Variance	6.851551957
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	22	56.4%
1	3	7.7%
4	3	7.7%
5	3	7.7%
3	2	5.1%
6	2	5.1%
8	2	5.1%
2	1	2.6%
7	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	22	56.4%
1	3	7.7%
2	1	2.6%
3	2	5.1%
4	3	7.7%
5	3	7.7%
6	2	5.1%
7	1	2.6%
8	2	5.1%

Value	Count	Frequency (%)
8	2	5.1%
7	1	2.6%
6	2	5.1%
5	3	7.7%
4	3	7.7%
3	2	5.1%
2	1	2.6%
1	3	7.7%
0	22	56.4%

Italy
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	10
Distinct (%)	25.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.282051282

Minimum	0
Maximum	12
Zeros	11
Zeros (%)	28.2%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	6
Q3	9
95-th percentile	12
Maximum	12
Range	12
Interquartile range (IQR)	9

Descriptive statistics

Standard deviation	4.248521216
Coefficient of variation (CV)	0.8043316865
Kurtosis	-1.349525721
Mean	5.282051282
Median Absolute Deviation (MAD)	4
Skewness	0.08455082259
Sum	206
Variance	18.04993252
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	11	28.2%
10	6	15.4%
6	5	12.8%
8	4	10.3%
12	4	10.3%
3	3	7.7%
4	2	5.1%
5	2	5.1%
2	1	2.6%
7	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	11	28.2%
2	1	2.6%
3	3	7.7%
4	2	5.1%
5	2	5.1%
6	5	12.8%
7	1	2.6%
8	4	10.3%
10	6	15.4%
12	4	10.3%

Value	Count	Frequency (%)
12	4	10.3%
10	6	15.4%
8	4	10.3%
7	1	2.6%
6	5	12.8%
5	2	5.1%
4	2	5.1%
3	3	7.7%
2	1	2.6%
0	11	28.2%

Lithuania
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	8
Distinct (%)	20.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.41025641

Minimum	0
Maximum	12
Zeros	27
Zeros (%)	69.2%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	2
95-th percentile	6.4
Maximum	12
Range	12
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.816473614
Coefficient of variation (CV)	1.997135835
Kurtosis	6.111380468
Mean	1.41025641
Median Absolute Deviation (MAD)	0
Skewness	2.461124479
Sum	55
Variance	7.932523617
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	27	69.2%
2	3	7.7%
3	2	5.1%
4	2	5.1%
6	2	5.1%
1	1	2.6%
10	1	2.6%
12	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	27	69.2%
1	1	2.6%
2	3	7.7%
3	2	5.1%
4	2	5.1%
6	2	5.1%
10	1	2.6%
12	1	2.6%

Value	Count	Frequency (%)
12	1	2.6%
10	1	2.6%
6	2	5.1%
4	2	5.1%
3	2	5.1%
2	3	7.7%
1	1	2.6%
0	27	69.2%

Malta
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	11
Distinct (%)	28.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.333333333

Minimum	0
Maximum	12
Zeros	4
Zeros (%)	10.3%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3
median	5
Q3	7
95-th percentile	12
Maximum	12
Range	12
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	3.55656053
Coefficient of variation (CV)	0.6668550995
Kurtosis	-0.5759857341
Mean	5.333333333
Median Absolute Deviation (MAD)	2
Skewness	0.2878738469
Sum	208
Variance	12.64912281
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
5	6	15.4%
7	6	15.4%
4	5	12.8%
0	4	10.3%
1	4	10.3%
12	4	10.3%
8	3	7.7%
3	2	5.1%
6	2	5.1%
10	2	5.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4	10.3%
1	4	10.3%
2	1	2.6%
3	2	5.1%
4	5	12.8%
5	6	15.4%
6	2	5.1%
7	6	15.4%
8	3	7.7%
10	2	5.1%

Value	Count	Frequency (%)
12	4	10.3%
10	2	5.1%
8	3	7.7%
7	6	15.4%
6	2	5.1%
5	6	15.4%
4	5	12.8%
3	2	5.1%
2	1	2.6%
1	4	10.3%

Moldova
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	6
Distinct (%)	15.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.358974359

Minimum	0
Maximum	12
Zeros	33
Zeros (%)	84.6%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	10.2
Maximum	12
Range	12
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	3.406550806
Coefficient of variation (CV)	2.506707197
Kurtosis	4.509724696
Mean	1.358974359
Median Absolute Deviation (MAD)	0
Skewness	2.395020275
Sum	53
Variance	11.60458839
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	33	84.6%
12	2	5.1%
5	1	2.6%
6	1	2.6%
8	1	2.6%
10	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	33	84.6%
5	1	2.6%
6	1	2.6%
8	1	2.6%
10	1	2.6%
12	2	5.1%

Value	Count	Frequency (%)
12	2	5.1%
10	1	2.6%
8	1	2.6%
6	1	2.6%
5	1	2.6%
0	33	84.6%

Netherlands
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	10.3%
Missing	0
Missing (%)	0.0%
Memory size	2.3 KiB

0	34
3	2
2	2
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	39
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	2.6%

Sample

1st row	0
2nd row	3
3rd row	3
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	34	87.2%
3	2	5.1%
2	2	5.1%
1	1	2.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	34	87.2%
3	2	5.1%
2	2	5.1%
1	1	2.6%

Most occurring characters

Value	Count	Frequency (%)
0	34	87.2%
3	2	5.1%
2	2	5.1%
1	1	2.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	39	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	34	87.2%
3	2	5.1%
2	2	5.1%
1	1	2.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	39	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	34	87.2%
3	2	5.1%
2	2	5.1%
1	1	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	39	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	34	87.2%
3	2	5.1%
2	2	5.1%
1	1	2.6%

Norway
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	12.8%
Missing	0
Missing (%)	0.0%
Memory size	2.3 KiB

0	34
2	2
3	1
7	1
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	39
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	7.7%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	34	87.2%
2	2	5.1%
3	1	2.6%
7	1	2.6%
1	1	2.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	34	87.2%
2	2	5.1%
3	1	2.6%
7	1	2.6%
1	1	2.6%

Most occurring characters

Value	Count	Frequency (%)
0	34	87.2%
2	2	5.1%
3	1	2.6%
7	1	2.6%
1	1	2.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	39	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	34	87.2%
2	2	5.1%
3	1	2.6%
7	1	2.6%
1	1	2.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	39	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	34	87.2%
2	2	5.1%
3	1	2.6%
7	1	2.6%
1	1	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	39	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	34	87.2%
2	2	5.1%
3	1	2.6%
7	1	2.6%
1	1	2.6%

Portugal
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	9
Distinct (%)	23.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.230769231

Minimum	0
Maximum	12
Zeros	17
Zeros (%)	43.6%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	6.5
95-th percentile	10
Maximum	12
Range	12
Interquartile range (IQR)	6.5

Descriptive statistics

Standard deviation	3.709600195
Coefficient of variation (CV)	1.148209584
Kurtosis	-0.8741908984
Mean	3.230769231
Median Absolute Deviation (MAD)	1
Skewness	0.7077415858
Sum	126
Variance	13.7611336
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	17	43.6%
7	4	10.3%
1	3	7.7%
2	3	7.7%
5	3	7.7%
6	3	7.7%
8	3	7.7%
10	2	5.1%
12	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	17	43.6%
1	3	7.7%
2	3	7.7%
5	3	7.7%
6	3	7.7%
7	4	10.3%
8	3	7.7%
10	2	5.1%
12	1	2.6%

Value	Count	Frequency (%)
12	1	2.6%
10	2	5.1%
8	3	7.7%
7	4	10.3%
6	3	7.7%
5	3	7.7%
2	3	7.7%
1	3	7.7%
0	17	43.6%

Russia
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	10
Distinct (%)	25.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.666666667

Minimum	0
Maximum	12
Zeros	18
Zeros (%)	46.2%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	4
95-th percentile	10
Maximum	12
Range	12
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	3.622541514
Coefficient of variation (CV)	1.358453068
Kurtosis	0.2662431513
Mean	2.666666667
Median Absolute Deviation (MAD)	1
Skewness	1.250500475
Sum	104
Variance	13.12280702
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	18	46.2%
1	4	10.3%
2	4	10.3%
10	3	7.7%
3	2	5.1%
4	2	5.1%
7	2	5.1%
8	2	5.1%
6	1	2.6%
12	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	18	46.2%
1	4	10.3%
2	4	10.3%
3	2	5.1%
4	2	5.1%
6	1	2.6%
7	2	5.1%
8	2	5.1%
10	3	7.7%
12	1	2.6%

Value	Count	Frequency (%)
12	1	2.6%
10	3	7.7%
8	2	5.1%
7	2	5.1%
6	1	2.6%
4	2	5.1%
3	2	5.1%
2	4	10.3%
1	4	10.3%
0	18	46.2%

San Marino
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	7
Distinct (%)	17.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.9487179487

Minimum	0
Maximum	12
Zeros	32
Zeros (%)	82.1%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	5.2
Maximum	12
Range	12
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	2.480966683
Coefficient of variation (CV)	2.61507299
Kurtosis	10.5168217
Mean	0.9487179487
Median Absolute Deviation (MAD)	0
Skewness	3.113326312
Sum	37
Variance	6.155195682
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	32	82.1%
5	2	5.1%
1	1	2.6%
3	1	2.6%
4	1	2.6%
7	1	2.6%
12	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	32	82.1%
1	1	2.6%
3	1	2.6%
4	1	2.6%
5	2	5.1%
7	1	2.6%
12	1	2.6%

Value	Count	Frequency (%)
12	1	2.6%
7	1	2.6%
5	2	5.1%
4	1	2.6%
3	1	2.6%
1	1	2.6%
0	32	82.1%

Serbia
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	10.3%
Missing	0
Missing (%)	0.0%
Memory size	2.3 KiB

0	36
12	1
1	1
7	1

Length

Max length	2
Median length	1
Mean length	1.025641026
Min length	1

Characters and Unicode

Total characters	40
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	7.7%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	36	92.3%
12	1	2.6%
1	1	2.6%
7	1	2.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	36	92.3%
12	1	2.6%
1	1	2.6%
7	1	2.6%

Most occurring characters

Value	Count	Frequency (%)
0	36	90.0%
1	2	5.0%
7	1	2.5%
2	1	2.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	40	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	36	90.0%
1	2	5.0%
7	1	2.5%
2	1	2.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	40	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	36	90.0%
1	2	5.0%
7	1	2.5%
2	1	2.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	40	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	36	90.0%
1	2	5.0%
7	1	2.5%
2	1	2.5%

Spain
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	7.7%
Missing	0
Missing (%)	0.0%
Memory size	2.3 KiB

0	37
4	1
2	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	39
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	5.1%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	37	94.9%
4	1	2.6%
2	1	2.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	37	94.9%
4	1	2.6%
2	1	2.6%

Most occurring characters

Value	Count	Frequency (%)
0	37	94.9%
4	1	2.6%
2	1	2.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	39	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	37	94.9%
4	1	2.6%
2	1	2.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	39	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	37	94.9%
4	1	2.6%
2	1	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	39	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	37	94.9%
4	1	2.6%
2	1	2.6%

Sweden
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	8
Distinct (%)	20.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.179487179

Minimum	0
Maximum	10
Zeros	29
Zeros (%)	74.4%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0.5
95-th percentile	5.3
Maximum	10
Range	10
Interquartile range (IQR)	0.5

Descriptive statistics

Standard deviation	2.41564849
Coefficient of variation (CV)	2.048049806
Kurtosis	4.803823382
Mean	1.179487179
Median Absolute Deviation (MAD)	0
Skewness	2.245981022
Sum	46
Variance	5.835357625
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	29	74.4%
4	3	7.7%
5	2	5.1%
1	1	2.6%
2	1	2.6%
3	1	2.6%
8	1	2.6%
10	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	29	74.4%
1	1	2.6%
2	1	2.6%
3	1	2.6%
4	3	7.7%
5	2	5.1%
8	1	2.6%
10	1	2.6%

Value	Count	Frequency (%)
10	1	2.6%
8	1	2.6%
5	2	5.1%
4	3	7.7%
3	1	2.6%
2	1	2.6%
1	1	2.6%
0	29	74.4%

Switzerland
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	11
Distinct (%)	28.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.846153846

Minimum	0
Maximum	12
Zeros	5
Zeros (%)	12.8%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	4.5
median	7
Q3	10
95-th percentile	12
Maximum	12
Range	12
Interquartile range (IQR)	5.5

Descriptive statistics

Standard deviation	4.107364769
Coefficient of variation (CV)	0.5999521572
Kurtosis	-1.037942335
Mean	6.846153846
Median Absolute Deviation (MAD)	3
Skewness	-0.3738740617
Sum	267
Variance	16.87044534
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
12	8	20.5%
7	6	15.4%
10	6	15.4%
0	5	12.8%
5	4	10.3%
8	4	10.3%
1	2	5.1%
2	1	2.6%
3	1	2.6%
4	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	5	12.8%
1	2	5.1%
2	1	2.6%
3	1	2.6%
4	1	2.6%
5	4	10.3%
6	1	2.6%
7	6	15.4%
8	4	10.3%
10	6	15.4%

Value	Count	Frequency (%)
12	8	20.5%
10	6	15.4%
8	4	10.3%
7	6	15.4%
6	1	2.6%
5	4	10.3%
4	1	2.6%
3	1	2.6%
2	1	2.6%
1	2	5.1%

Ukraine
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	11
Distinct (%)	28.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.487179487

Minimum	0
Maximum	12
Zeros	20
Zeros (%)	51.3%
Negative	0
Negative (%)	0.0%
Memory size	440.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	5
95-th percentile	8.2
Maximum	12
Range	12
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.251491924
Coefficient of variation (CV)	1.307300877
Kurtosis	0.7123684499
Mean	2.487179487
Median Absolute Deviation (MAD)	0
Skewness	1.193700458
Sum	97
Variance	10.57219973
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	20	51.3%
5	4	10.3%
3	3	7.7%
1	2	5.1%
4	2	5.1%
6	2	5.1%
7	2	5.1%
2	1	2.6%
8	1	2.6%
10	1	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	20	51.3%
1	2	5.1%
2	1	2.6%
3	3	7.7%
4	2	5.1%
5	4	10.3%
6	2	5.1%
7	2	5.1%
8	1	2.6%
10	1	2.6%

Value	Count	Frequency (%)
12	1	2.6%
10	1	2.6%
8	1	2.6%
7	2	5.1%
6	2	5.1%
5	4	10.3%
4	2	5.1%
3	3	7.7%
2	1	2.6%
1	2	5.1%

United Kingdom
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	2.6%
Missing	0
Missing (%)	0.0%
Memory size	2.3 KiB

0	39

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	39
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	39	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	39	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	39	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	39	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	39	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	39	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	39	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	39	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	39	100.0%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	Country (Voters (vertical), Finalists (horizontal))	Albania	Azerbaijan	Belgium	Bulgaria	Cyprus	Finland	France	Germany	Greece	Iceland	Israel	Italy	Lithuania	Malta	Moldova	Netherlands	Norway	Portugal	Russia	San Marino	Serbia	Spain	Sweden	Switzerland	Ukraine
0	Albania	0	0	0	0	7	3	10	0	6	0	0	4	0	8	0	0	0	0	0	5	1	0	0	12	0
1	Australia	0	6	0	2	4	0	7	0	0	8	0	6	0	12	0	3	0	0	1	0	0	0	0	10	5
2	Austria	0	0	0	5	0	1	8	2	0	12	0	6	0	4	0	3	0	7	0	0	0	0	0	10	0
3	Azerbaijan	0	0	3	1	0	0	4	0	10	0	0	0	0	7	8	0	0	2	12	0	0	0	5	0	6
4	Belgium	0	0	0	6	0	8	0	0	0	3	0	2	0	5	0	0	0	1	7	0	0	0	4	12	10
5	Bulgaria	0	0	0	0	0	1	7	0	8	0	3	10	0	5	12	2	0	6	0	0	0	4	0	0	0
6	Croatia	0	0	0	0	0	0	6	0	0	10	5	12	2	3	0	0	0	1	4	0	7	0	0	8	0
7	Cyprus	0	2	4	5	0	3	7	0	12	0	0	8	0	10	0	0	0	1	6	0	0	0	0	2	0
8	Czechia	0	8	3	4	0	1	10	0	0	8	0	6	0	7	0	0	0	12	2	0	0	0	0	5	0
9	Denmark	7	0	0	6	0	8	0	0	0	10	1	0	0	4	0	0	3	0	0	5	0	0	2	12	0

Last rows

	Country (Voters (vertical), Finalists (horizontal))	Albania	Azerbaijan	Belgium	Bulgaria	Cyprus	Finland	France	Germany	Greece	Iceland	Israel	Italy	Lithuania	Malta	Moldova	Norway	Portugal	Russia	San Marino	Spain	Sweden	Switzerland	Ukraine
29	Romania	0	0	0	2	0	8	4	1	0	0	0	3	0	12	6	0	10	0	0	0	0	7	5
30	Russia	0	0	3	6	2	0	0	0	7	0	5	10	0	4	12	0	0	0	0	0	0	1	0
31	San Marino	2	0	0	3	0	1	12	0	8	0	0	10	6	7	5	0	0	0	0	0	0	4	0
32	Serbia	0	2	0	6	0	10	12	0	3	7	2	8	0	0	0	0	5	0	0	0	4	1	0
33	Slovenia	0	5	6	0	0	4	2	0	3	10	1	12	0	5	0	0	0	8	0	0	0	7	0
34	Spain	0	0	0	4	6	0	12	0	1	7	3	0	2	8	0	0	5	0	0	0	0	10	0
35	Sweden	0	0	1	0	0	0	6	0	0	7	4	10	0	12	0	2	0	3	0	0	0	5	8
36	Switzerland	0	3	0	10	0	1	12	0	0	5	0	8	4	6	0	0	7	3	0	0	0	0	0
37	Ukraine	0	0	6	0	0	0	10	0	0	4	7	12	0	5	0	1	2	0	0	0	0	8	0
38	United Kingdom	0	0	1	5	0	4	12	0	0	10	6	0	0	0	0	0	7	0	3	2	0	8	0

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks